On the parameterization of acoustic detection probability models

Summary Methods that aid in understanding the variation in the detection probability in acoustic telemetry can aid proper interpretations of data derived using such systems. In their recent paper, Huveneers et al. (Methods in Ecology and Evolution, 7, 825‐835, 2016) claim that a general detection pr...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Methods in ecology and evolution 2017-10, Vol.8 (10), p.1302-1304
Hauptverfasser: Gjelland, Karl Ø., Hedger, Richard D., Reynolds, John
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1304
container_issue 10
container_start_page 1302
container_title Methods in ecology and evolution
container_volume 8
creator Gjelland, Karl Ø.
Hedger, Richard D.
Reynolds, John
description Summary Methods that aid in understanding the variation in the detection probability in acoustic telemetry can aid proper interpretations of data derived using such systems. In their recent paper, Huveneers et al. (Methods in Ecology and Evolution, 7, 825‐835, 2016) claim that a general detection probability model (Gjelland & Hedger, Methods in Ecology and Evolution, 4, 665–674, 2013) does not have the intended applicability across systems. However, Huveneer et al. applies predictions for a shallow freshwater application to results from a much deeper marine application, which is an invalid use of acoustic theory and the proposed general model. Users of acoustic telemetry are encouraged to acknowledge how environmentally induced variation in the acoustic attenuation coefficient influences the detection probability, because an understanding of this will aid prediction of how acoustic telemetry systems will work under various environmental conditions. Models used for predictions must be appropriately parameterized. Proper incorporation of spatiotemporal variation in acoustic detection probability may help reduce effects of environmentally induced biases in detection data. We challenge scientists to make further contributions to how acoustic theory can be incorporated in the modelling of detection probability in acoustic telemetry.
doi_str_mv 10.1111/2041-210X.12732
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_1950003427</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1950003427</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3572-a78d0679d006cc8c60905e4d5b2d80a4b91c9556284c2ddabd144c5ce504940b3</originalsourceid><addsrcrecordid>eNqFUE1LxDAQDaLgUvfsteC5u5M0aZubstQPWNmLgreQJilmaTdr0kXWX2-6FfHmu8ww8958PISuMSxwxJIAxRnB8LbApMzJGZr9Vs7_5JdoHsIWIvKKA6EzdLvZpcO7SffSy94MxtsvOVi3S12bSuUOYbAq1bGhTtW9d41sbGeHY9o7bbpwhS5a2QUz_4kJer2vX1aP2Xrz8LS6W2cqZyXJZFlpKEquAQqlKlUAB2aoZg3RFUjacKw4YwWpqCJay0ZjShVThgHlFJo8QTfT3HjCx8GEQWzdwe_iSoE5Gz-i8fMELSeW8i4Eb1qx97aX_igwiNEpMXohRi_EyamoKCbFp-3M8T-6eK7rfBJ-A9YeaeI</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1950003427</pqid></control><display><type>article</type><title>On the parameterization of acoustic detection probability models</title><source>Access via Wiley Online Library</source><source>Alma/SFX Local Collection</source><creator>Gjelland, Karl Ø. ; Hedger, Richard D. ; Reynolds, John</creator><contributor>Reynolds, John</contributor><creatorcontrib>Gjelland, Karl Ø. ; Hedger, Richard D. ; Reynolds, John ; Reynolds, John</creatorcontrib><description>Summary Methods that aid in understanding the variation in the detection probability in acoustic telemetry can aid proper interpretations of data derived using such systems. In their recent paper, Huveneers et al. (Methods in Ecology and Evolution, 7, 825‐835, 2016) claim that a general detection probability model (Gjelland &amp; Hedger, Methods in Ecology and Evolution, 4, 665–674, 2013) does not have the intended applicability across systems. However, Huveneer et al. applies predictions for a shallow freshwater application to results from a much deeper marine application, which is an invalid use of acoustic theory and the proposed general model. Users of acoustic telemetry are encouraged to acknowledge how environmentally induced variation in the acoustic attenuation coefficient influences the detection probability, because an understanding of this will aid prediction of how acoustic telemetry systems will work under various environmental conditions. Models used for predictions must be appropriately parameterized. Proper incorporation of spatiotemporal variation in acoustic detection probability may help reduce effects of environmentally induced biases in detection data. We challenge scientists to make further contributions to how acoustic theory can be incorporated in the modelling of detection probability in acoustic telemetry.</description><identifier>ISSN: 2041-210X</identifier><identifier>EISSN: 2041-210X</identifier><identifier>DOI: 10.1111/2041-210X.12732</identifier><language>eng</language><publisher>London: John Wiley &amp; Sons, Inc</publisher><subject>Acoustic attenuation ; Acoustic telemetry ; Acoustics ; animal tracking ; Attenuation coefficients ; behavioural ecology ; biotelemetry ; Coefficient of variation ; Data processing ; Ecology ; Environment models ; Environmental conditions ; environmental effects ; Evolution ; habitat use ; movement ecology ; Owls ; Parameterization ; Probabilistic methods ; Sound detecting and ranging ; Telemetry ; Variation</subject><ispartof>Methods in ecology and evolution, 2017-10, Vol.8 (10), p.1302-1304</ispartof><rights>2017 The Authors. Methods in Ecology and Evolution © 2017 British Ecological Society</rights><rights>Methods in Ecology and Evolution © 2017 British Ecological Society</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3572-a78d0679d006cc8c60905e4d5b2d80a4b91c9556284c2ddabd144c5ce504940b3</citedby><cites>FETCH-LOGICAL-c3572-a78d0679d006cc8c60905e4d5b2d80a4b91c9556284c2ddabd144c5ce504940b3</cites><orcidid>0000-0003-4036-4207</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2F2041-210X.12732$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2F2041-210X.12732$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids></links><search><contributor>Reynolds, John</contributor><creatorcontrib>Gjelland, Karl Ø.</creatorcontrib><creatorcontrib>Hedger, Richard D.</creatorcontrib><creatorcontrib>Reynolds, John</creatorcontrib><title>On the parameterization of acoustic detection probability models</title><title>Methods in ecology and evolution</title><description>Summary Methods that aid in understanding the variation in the detection probability in acoustic telemetry can aid proper interpretations of data derived using such systems. In their recent paper, Huveneers et al. (Methods in Ecology and Evolution, 7, 825‐835, 2016) claim that a general detection probability model (Gjelland &amp; Hedger, Methods in Ecology and Evolution, 4, 665–674, 2013) does not have the intended applicability across systems. However, Huveneer et al. applies predictions for a shallow freshwater application to results from a much deeper marine application, which is an invalid use of acoustic theory and the proposed general model. Users of acoustic telemetry are encouraged to acknowledge how environmentally induced variation in the acoustic attenuation coefficient influences the detection probability, because an understanding of this will aid prediction of how acoustic telemetry systems will work under various environmental conditions. Models used for predictions must be appropriately parameterized. Proper incorporation of spatiotemporal variation in acoustic detection probability may help reduce effects of environmentally induced biases in detection data. We challenge scientists to make further contributions to how acoustic theory can be incorporated in the modelling of detection probability in acoustic telemetry.</description><subject>Acoustic attenuation</subject><subject>Acoustic telemetry</subject><subject>Acoustics</subject><subject>animal tracking</subject><subject>Attenuation coefficients</subject><subject>behavioural ecology</subject><subject>biotelemetry</subject><subject>Coefficient of variation</subject><subject>Data processing</subject><subject>Ecology</subject><subject>Environment models</subject><subject>Environmental conditions</subject><subject>environmental effects</subject><subject>Evolution</subject><subject>habitat use</subject><subject>movement ecology</subject><subject>Owls</subject><subject>Parameterization</subject><subject>Probabilistic methods</subject><subject>Sound detecting and ranging</subject><subject>Telemetry</subject><subject>Variation</subject><issn>2041-210X</issn><issn>2041-210X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNqFUE1LxDAQDaLgUvfsteC5u5M0aZubstQPWNmLgreQJilmaTdr0kXWX2-6FfHmu8ww8958PISuMSxwxJIAxRnB8LbApMzJGZr9Vs7_5JdoHsIWIvKKA6EzdLvZpcO7SffSy94MxtsvOVi3S12bSuUOYbAq1bGhTtW9d41sbGeHY9o7bbpwhS5a2QUz_4kJer2vX1aP2Xrz8LS6W2cqZyXJZFlpKEquAQqlKlUAB2aoZg3RFUjacKw4YwWpqCJay0ZjShVThgHlFJo8QTfT3HjCx8GEQWzdwe_iSoE5Gz-i8fMELSeW8i4Eb1qx97aX_igwiNEpMXohRi_EyamoKCbFp-3M8T-6eK7rfBJ-A9YeaeI</recordid><startdate>201710</startdate><enddate>201710</enddate><creator>Gjelland, Karl Ø.</creator><creator>Hedger, Richard D.</creator><creator>Reynolds, John</creator><general>John Wiley &amp; Sons, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QG</scope><scope>7SN</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><orcidid>https://orcid.org/0000-0003-4036-4207</orcidid></search><sort><creationdate>201710</creationdate><title>On the parameterization of acoustic detection probability models</title><author>Gjelland, Karl Ø. ; Hedger, Richard D. ; Reynolds, John</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3572-a78d0679d006cc8c60905e4d5b2d80a4b91c9556284c2ddabd144c5ce504940b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Acoustic attenuation</topic><topic>Acoustic telemetry</topic><topic>Acoustics</topic><topic>animal tracking</topic><topic>Attenuation coefficients</topic><topic>behavioural ecology</topic><topic>biotelemetry</topic><topic>Coefficient of variation</topic><topic>Data processing</topic><topic>Ecology</topic><topic>Environment models</topic><topic>Environmental conditions</topic><topic>environmental effects</topic><topic>Evolution</topic><topic>habitat use</topic><topic>movement ecology</topic><topic>Owls</topic><topic>Parameterization</topic><topic>Probabilistic methods</topic><topic>Sound detecting and ranging</topic><topic>Telemetry</topic><topic>Variation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gjelland, Karl Ø.</creatorcontrib><creatorcontrib>Hedger, Richard D.</creatorcontrib><creatorcontrib>Reynolds, John</creatorcontrib><collection>CrossRef</collection><collection>Animal Behavior Abstracts</collection><collection>Ecology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><jtitle>Methods in ecology and evolution</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gjelland, Karl Ø.</au><au>Hedger, Richard D.</au><au>Reynolds, John</au><au>Reynolds, John</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>On the parameterization of acoustic detection probability models</atitle><jtitle>Methods in ecology and evolution</jtitle><date>2017-10</date><risdate>2017</risdate><volume>8</volume><issue>10</issue><spage>1302</spage><epage>1304</epage><pages>1302-1304</pages><issn>2041-210X</issn><eissn>2041-210X</eissn><abstract>Summary Methods that aid in understanding the variation in the detection probability in acoustic telemetry can aid proper interpretations of data derived using such systems. In their recent paper, Huveneers et al. (Methods in Ecology and Evolution, 7, 825‐835, 2016) claim that a general detection probability model (Gjelland &amp; Hedger, Methods in Ecology and Evolution, 4, 665–674, 2013) does not have the intended applicability across systems. However, Huveneer et al. applies predictions for a shallow freshwater application to results from a much deeper marine application, which is an invalid use of acoustic theory and the proposed general model. Users of acoustic telemetry are encouraged to acknowledge how environmentally induced variation in the acoustic attenuation coefficient influences the detection probability, because an understanding of this will aid prediction of how acoustic telemetry systems will work under various environmental conditions. Models used for predictions must be appropriately parameterized. Proper incorporation of spatiotemporal variation in acoustic detection probability may help reduce effects of environmentally induced biases in detection data. We challenge scientists to make further contributions to how acoustic theory can be incorporated in the modelling of detection probability in acoustic telemetry.</abstract><cop>London</cop><pub>John Wiley &amp; Sons, Inc</pub><doi>10.1111/2041-210X.12732</doi><tpages>3</tpages><orcidid>https://orcid.org/0000-0003-4036-4207</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2041-210X
ispartof Methods in ecology and evolution, 2017-10, Vol.8 (10), p.1302-1304
issn 2041-210X
2041-210X
language eng
recordid cdi_proquest_journals_1950003427
source Access via Wiley Online Library; Alma/SFX Local Collection
subjects Acoustic attenuation
Acoustic telemetry
Acoustics
animal tracking
Attenuation coefficients
behavioural ecology
biotelemetry
Coefficient of variation
Data processing
Ecology
Environment models
Environmental conditions
environmental effects
Evolution
habitat use
movement ecology
Owls
Parameterization
Probabilistic methods
Sound detecting and ranging
Telemetry
Variation
title On the parameterization of acoustic detection probability models
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-22T19%3A45%3A11IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=On%20the%20parameterization%20of%20acoustic%20detection%20probability%20models&rft.jtitle=Methods%20in%20ecology%20and%20evolution&rft.au=Gjelland,%20Karl%20%C3%98.&rft.date=2017-10&rft.volume=8&rft.issue=10&rft.spage=1302&rft.epage=1304&rft.pages=1302-1304&rft.issn=2041-210X&rft.eissn=2041-210X&rft_id=info:doi/10.1111/2041-210X.12732&rft_dat=%3Cproquest_cross%3E1950003427%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1950003427&rft_id=info:pmid/&rfr_iscdi=true